Abstract: Graph Neural Networks (GNNs) have become a powerful tool in order to learn from graph-structured data. Their ability to capture complex relationships and dependencies within graph structures ...
STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
NCP is a versioned, transport-agnostic wire contract that lets a running NEST network — point neurons (spiking, binary) and rate-based models — serve external robot, UAV, and analysis clients — for ...
Abstract: The improvement of fault diagnosis for complex equipment is an important step towards intelligent systems. Unlike component-level fault detection, system-level fault diagnosis presents new ...
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